Nevertheless, we used various traditional SER classifiers such as HMM (Hidden Markov Model), GMM (Gaussian Mixture Model), k-Nearest Neighbour (kNN), and Artificial Neural Networks (ANN) [1]} for evaluating their performance on the three Emotional Speech Sets. As depicted in Table: REF , the average emotion classification rate using SVM classifier for Bangla, English and English_TESS Speech Sets supersedes the other traditional classifiers, HMM, GMM, kNN, and ANN. Therefore, in this study, we adopted a generic SVM kernel analogous to the classifiers deployed in SER to generate a non-linear hyperplane for recognizing the six emotional states. Additionally, we deliberately eschewed using Deep Learning based classifiers due to over-fitting complexities and preliminary processing of the Emotional Speech Sets.
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